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ImageJ is a Java-based image processing program developed at the National Institutes of Health and the Laboratory for Optical and Computational Instrumentation (LOCI, University of Wisconsin). [ 2 ] [ 3 ] Its first version, ImageJ 1.x, is developed in the public domain , while ImageJ2 and the related projects SciJava , ImgLib2 , and SCIFIO are ...
One of Fiji's principal aims is to make the installation of ImageJ, Java, Java 3D, the plugins, and further convenient components, as easy as possible. As a consequence, Fiji enjoys more and more active users.
In addition, Bio7 also contains a complete graphical user interface for the statistical R programming language [2] and the scientific image analysis tool ImageJ [3] with special functions to send image data from ImageJ to R or R data to ImageJ. It is considered a diverging fork of ImageJ to improve the UI integration. [4]
In computer science, a for-loop or for loop is a control flow statement for specifying iteration. Specifically, a for-loop functions by running a section of code repeatedly until a certain condition has been satisfied. For-loops have two parts: a header and a body. The header defines the iteration and the body is the code executed once per ...
ImageJ Macro language, a programming language International Justice Mission , a non-profit human rights organization Institut Jacques Monod , a research institute in Paris, France
First created in 2001 by Mathias Roth, [8] [9] iMacros was the first macro recorder tool specifically designed and optimized for web browsers [10] and form filling. [11] In April 2012 iMacros was acquired [12] by Ipswitch. In 2019 Ipswitch itself (and thus iMacros along with it) was acquired by Progress. [13] In November 2022 Progress ...
A plugin for ImageJ using Otsu's method to do the threshold; A full explanation of Otsu's method with a working example and Java implementation; Implementation of Otsu's method in ITK; Otsu Thresholding in C# – a straightforward C# implementation with explanation; Otsu's method using MATLAB; Otsu Thresholding with scikit-image in Python
Connected-component labeling (CCL), connected-component analysis (CCA), blob extraction, region labeling, blob discovery, or region extraction is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic.